Conditional Confidence Intervals Of Process Capability Indices Following Rejection Of Preliminary Tests
2010
- 20Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Thesis / Dissertation Description
Finding an ordinary confidence interval of an unknown parameter is well known, but finding a conditional confidence interval following rejection of a preliminary test is not so noted, especially for finding a conditional confidence interval of the process capability indices Cp or Cpk following rejection of some preliminary tests. This dissertation will provide some basic theories and computational methods for finding such conditional confidence intervals of the two process capability indices. The most basic method used in this dissertation is the general method for finding a confidence interval of an unknown parameter. Numerical methods are also used for finding the values of these conditional confidence limits. The conditional confidence intervals of the process capability index Cp and Cpk are obtained. Computational programming code and other useful information and methods are provided.
Bibliographic Details
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